System and method for digital signal processing

ABSTRACT

The present invention provides for methods and systems for digitally processing an audio signal. In various embodiments, a method comprises receiving a profile comprising a plurality of filter equalizing coefficients, configuring a plurality of filters of a graphic equalizer with the plurality of filter equalizing coefficients from the profile, receiving a first signal for processing, adjusting the plurality of filters using a first gain, equalizing the first signal using the plurality of filters of the graphic equalizer, outputting the first signal, receiving a second signal for processing, adjusting the plurality of filters, previously configured with the filter equalizing coefficients from the profile, using a second gain, equalizing the second plurality of frequencies of the second signal with the plurality of filters of the graphic equalizer, and outputting the second signal.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. application Ser. No.11/947,301, filed June Nov. 29, 2007, which claims priority to U.S.Provisional Application No. 60/861,711 filed Nov. 30, 2006, and is acontinuation-in-part of U.S. application Ser. No. 11/703,216, filed Feb.7, 2007, which claims priority to U.S. Provisional Application No.60/765,722, filed Feb. 7, 2006. Each of the above applications isincorporated by reference herein in its entirety.

FIELD OF THE INVENTION

The present invention provides for methods and systems for digitallyprocessing an audio signal. Specifically, some embodiments relate todigitally processing an audio signal in a manner such thatstudio-quality sound that can be reproduced across the entire spectrumof audio devices.

BACKGROUND OF THE INVENTION

Historically, studio-quality sound, which can best be described as thefull reproduction of the complete range of audio frequencies that areutilized during the studio recording process, has only been able to beachieved, appropriately, in audio recording studios. Studio-qualitysound is characterized by the level of clarity and brightness which isattained only when the upper-mid frequency ranges are effectivelymanipulated and reproduced. While the technical underpinnings ofstudio-quality sound can be fully appreciated only by experienced recordproducers, the average listener can easily hear the difference thatstudio-quality sound makes.

While various attempts have been made to reproduce studio-quality soundoutside of the recording studio, those attempts have come at tremendousexpense (usually resulting from advanced speaker design, costlyhardware, and increased power amplification) and have achieved onlymixed results. Thus, there exists a need for a process wherebystudio-quality sound can be reproduced outside of the studio withconsistent, high quality, results at a low cost. There exists a furtherneed for audio devices embodying such a process, as well as computerchips embodying such a process that may be embedded within audiodevices. There also exists a need for the ability to producestudio-quality sound through inexpensive speakers.

In cellular telephones, little has been done to enhance and optimize theaudio quality of the voice during a conversation or of audio programmingduring playback. Manufacturers have, in some cases, attempted to enhancethe audio, but generally this is accomplished utilizing the volumecontrol of the device. The general clarity of the voice ‘sound’ remainsfixed. The voice is merely amplified and/or equalized. Moreover, thesettings for amplification and/or equalization are also fixed and cannotbe altered by the user.

Further, the design of audio systems for vehicles involves theconsideration of many different factors. The audio system designerselects the position and number of speakers in the vehicle. The desiredfrequency response of each speaker must also be determined. For example,the desired frequency response of a speaker that is located on theinstrument panel may be different than the desired frequency response ofa speaker that is located on the lower portion of the rear door panel.

The audio system designer must also consider how equipment variationsimpact the audio system. For example, an audio system in a convertiblemay not sound as good as the same audio system in the same model vehiclethat is a hard top. The audio system options for the vehicle may alsovary significantly. One audio option for the vehicle may include a basic4-speaker system with 40 watts amplification per channel while anotheraudio option may include a 12-speaker system with 200 wattsamplification per channel. The audio system designer must consider allof these configurations when designing the audio system for the vehicle.For these reasons, the design of audio systems is time consuming andcostly. The audio system designers must also have a relatively extensivebackground in signal processing and equalization.

Given those considerations, in order to achieve something approachingstudio-quality sound in a vehicle historically one would have required aconsiderable outlay of money, including expensive upgrades of thefactory-installed speakers. As such, there is a need for a system thatcan reproduce studio-quality sound in a vehicle without having to makesuch expensive outlays.

SUMMARY OF THE INVENTION

The present invention meets the existing needs described above byproviding for a method of digitally processing an audio signal in amanner such that studio-quality sound that can be reproduced across theentire spectrum of audio devices. The present invention also providesfor a computer chip that can digitally processing an audio signal issuch a manner, and provides for audio devices that comprise such a chip.

The present invention further meets the above stated needs by allowinginexpensive speakers to be used in the reproduction of studio-qualitysound. Furthermore, the present invention meets the existing needsdescribed above by providing for a mobile audio device that can be usedin a vehicle to reproduce studio-quality sound using the vehicle'sexisting speaker system by digitally manipulating audio signals. Indeed,even the vehicle's factory-installed speakers can be used to achievestudio-quality sound using the present invention.

In one embodiment, the present invention provides for a methodcomprising the steps of inputting an audio signal, adjusting the gain ofthat audio signal a first time, processing that signal with a first lowshelf filter, processing that signal with a first high shelf filter,processing that signal with a first compressor, processing that signalwith a second low shelf filter, processing that signal with a secondhigh shelf filter, processing that signal with a graphic equalizer,processing that signal with a second compressor, and adjusting the gainof that audio signal a second time. In this embodiment, the audio signalis manipulated such that studio-quality sound is produced. Further, thisembodiment compensates for any inherent volume differences that mayexist between audio sources or program material, and produces a constantoutput level of rich, full sound.

This embodiment also allows the studio-quality sound to be reproduced inhigh-noise environments, such as moving automobiles. Some embodiments ofthe present invention allow studio-quality sound to be reproduced in anyenvironment. This includes environments that are well designed withrespect to acoustics, such as, without limitation, a concert hall. Thisalso includes environments that are poorly designed with respect toacoustics, such as, without limitation, a traditional living room, theinterior of vehicles and the like. Further, some embodiments of thepresent invention allow the reproduction of studio-quality soundirrespective of the quality of the electronic components and speakersused in association with the present invention. Thus, the presentinvention can be used to reproduce studio-quality sound with bothtop-of-the-line and bottom-of-the-line electronics and speakers, andwith everything in between.

In some embodiments, this embodiment may be used for playing music,movies, or video games in high-noise environments such as, withoutlimitation, an automobile, airplane, boat, club, theatre, amusementpark, or shopping center. Furthermore, in some embodiments, the presentinvention seeks to improve sound presentation by processing an audiosignal outside the efficiency range of both the human ear and audiotransducers which is between approximately 600 Hz and approximately1,000 Hz. By processing audio outside this range, a fuller and broaderpresentation may be obtained.

In some embodiments, the bass portion of the audio signal may be reducedbefore compression and enhanced after compression, thus ensuring thatthe sound presented to the speakers has a spectrum rich in bass tonesand free of the muffling effects encountered with conventionalcompression. Furthermore, in some embodiments, as the dynamic range ofthe audio signal has been reduced by compression, the resulting outputmay be presented within a limited volume range. For example, the presentinvention may comfortably present studio-quality sound in a high-noiseenvironment with an 80 dB noise floor and a 110 dB sound threshold.

In some embodiments, the method specified above may be combined withover digital signal processing methods that are perform before theabove-recited method, after the above-recited method, or intermittentlywith the above-recited method.

In another specific embodiment, the present invention provides for acomputer chip that may perform the method specified above. In oneembodiment, the computer chip may be a digital signal processor, or DSP.In other embodiments, the computer chip may be any processor capable ofperforming the above-stated method, such as, without limitation, acomputer, computer software, an electrical circuit, an electrical chipprogrammed to perform these steps, or any other means to perform themethod described.

In another embodiment, the present invention provides for an audiodevice that comprises such a computer chip. The audio device maycomprise, for example and without limitation: a radio; a CD player; atape player; an MP3 player; a cell phone; a television; a computer; apublic address system; a game station such as a Playstation 3 (SonyCorporation—Tokyo, Japan), an X-Box 360 (Microsoft Corporation—Redmond,Wash.), or a Nintendo Wii (Nintendo Co., Ltd. Kyoto, Japan); a hometheater system; a DVD player; a video cassette player; or a Blu-Rayplayer.

In such an embodiment, the chip of the present invention may bedelivered the audio signal after it passes through the source selectorand before it reaches the volume control. Specifically, in someembodiments the chip of the present invention, located in the audiodevice, processes audio signals from one or more sources including,without limitation, radios, CD players, tape players, DVD players, andthe like. The output of the chip of the present invention may driveother signal processing modules or speakers, in which case signalamplification is often employed.

Specifically, in one embodiment, the present invention provides for amobile audio device that comprises such a computer chip. Such a mobileaudio device may be placed in an automobile, and may comprise, forexample and without limitation, a radio, a CD player, a tape player, anMP3 player, a DVD player, or a video cassette player.

In this embodiment, the mobile audio device of the present invention maybe specifically tuned to each vehicle it may be used in to obtainoptimum performance and to account for unique acoustic properties ineach vehicle such as speaker placement, passenger compartment design,and background noise. Also in this embodiment, the mobile audio deviceof the present invention may provide precision tuning for all 4independently controlled channels. Also in this embodiment, the mobileaudio device of the present invention may deliver about 200 watts ofpower. Also in this embodiment, the mobile audio device of the presentinvention may use the vehicle's existing (sometimes factory-installed)speaker system to produce studio-quality sound. Also in this embodiment,the mobile audio device of the present invention may comprise a USB portto allow songs in standard digital formats to be played. Also in thisembodiment, the mobile audio device of the present invention maycomprise an adapter for use with satellite radio. Also in thisembodiment, the mobile audio device of the present invention maycomprise an adaptor for use with existing digital audio playback devicessuch as, without limitation, MP3 players. Also in this embodiment, themobile audio device of the present invention may comprise a remotecontrol. Also in this embodiment, the mobile audio device of the presentinvention may comprise a detachable faceplate.

In various embodiments, a method comprises receiving a profilecomprising a plurality of filter equalizing coefficients, configuring aplurality of filters of a graphic equalizer with the plurality of filterequalizing coefficients from the profile, receiving a first signal forprocessing, adjusting the plurality of filters using a first gain,equalizing the first signal using the plurality of filters of thegraphic equalizer, outputting the first signal, receiving a secondsignal for processing, adjusting the plurality of filters, previouslyconfigured with the filter equalizing coefficients from the profile,using a second gain, equalizing the second plurality of frequencies ofthe second signal with the plurality of filters of the graphicequalizer, and outputting the second signal. The profile may be receivedfrom a communication network and/or from firmware.

The plurality of filters may be configured using the plurality of filterequalizing coefficients to modify the first signal to clarify a sound ofa voice during a telephone communication, to modify the first signal toclarify a sound of a voice in a high noise environment, and/or to modifythe first signal to adjust a sound associated with a media file for ahandheld device.

Prior to equalizing the first signal, the method may further compriseadjusting a gain of the first signal, filtering the adjusted firstsignal with a low shelf filter, and compressing the filtered firstsignal with a compressor. Further, the method may comprise, afterequalizing the first signal, compressing the equalized first signal witha compressor, and adjusting the gain of the compressed first signal.

In some embodiments, the method further comprises filtering the firstsignal with a first low filter, filtering the first signal received fromthe first low shelf filter with a first high shelf filter prior tocompressing the filtered signal with a compressor, filtering the firstsignal with a second low shelf filter prior to equalizing the firstsignal with the graphic equalizer, and filtering the first signal with asecond high shelf filter after the first signal is filtered with thesecond low shelf filter.

The plurality of filters of the graphic equalizer may comprise elevencascading second order filters. Each of the second order filters may bebell filters.

In some embodiments, a system comprises a graphic equalizer. The graphicequalizer may comprise a filter module, a profile module, and anequalizing module. The filter module comprises a plurality of filters.The profile module may be configured to receive a profile comprising aplurality of filter equalizing coefficients. The equalizing module maybe configured to configure the plurality of filters with the pluralityof filter equalizing coefficients from the profile, to receive first andsecond signals, to adjust the plurality of filters using a first gain,to equalize the first plurality using the plurality of filters of thegraphic equalizer, to output the first signal, to adjust the pluralityof filters, previously configured with the filter equalizingcoefficients from the profile, using a second gain, to equalize thesecond signal using the plurality of filters of the graphic equalizer,and to output the second signal.

In various embodiments, a method comprises configuring a graphicequalizer with a plurality of filter equalizing coefficients, adjustingthe graphic equalizer using a first gain, processing the first signalwith the graphic equalizer, outputting the first signal from the graphicequalizer, adjusting the graphic equalizer using a second gain,processing the second signal with the graphic equalizer, the graphicequalizer being previously configured with the plurality of filterequalizing coefficients, and outputting the second signal from thegraphic equalizer.

In some embodiments, a computer readable medium may comprise executableinstructions. The instructions may be executable by a processor forperforming a method. The method may comprise receiving a profilecomprising a plurality of filter equalizing coefficients, configuring aplurality of filters of a graphic equalizer using the plurality offilter equalizing coefficients from the profile, receiving a firstsignal for processing, adjusting the plurality of filters using a firstgain, equalizing the first signal using the plurality of filters of thegraphic equalizer, outputting the first signal, receiving a secondsignal for processing, adjusting the plurality of filters, previouslyconfigured using the filter coefficients from the profile, using asecond gain, equalizing the second plurality of frequencies of thesecond signal with the plurality of filters of the graphic equalizer,and outputting the second signal.

Other features and aspects of the invention will become apparent fromthe following detailed description, taken in conjunction with theaccompanying drawings, which illustrate, by way of example, the featuresin accordance with embodiments of the invention. The summary is notintended to limit the scope of the invention, which is defined solely bythe claims attached hereto.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention, in accordance with one or more variousembodiments, is described in detail with reference to the followingfigures. The drawings are provided for purposes of illustration only andmerely depict typical or example embodiments of the invention. Thesedrawings are provided to facilitate the reader's understanding of theinvention and shall not be considered limiting of the breadth, scope, orapplicability of the invention. It should be noted that for clarity andease of illustration these drawings are not necessarily made to scale.

FIG. 1 shows a block diagram of one embodiment of the digital signalprocessing method of the present invention.

FIG. 2 shows the effect of a low-shelf filter used in one embodiment ofthe digital signal processing method of the present invention.

FIG. 3 shows how a low-shelf filter can be created using high-pass andlow-pass filters.

FIG. 4 shows the effect of a high-shelf filter used in one embodiment ofthe digital signal processing method of the present invention.

FIG. 5 shows the frequency response of a bell filter used in oneembodiment of the digital signal processing method of the presentinvention.

FIG. 6 shows a block diagram of one embodiment of a graphic equalizerused in one embodiment of the digital signal processing method of thepresent invention.

FIG. 7 shows a block diagram showing how a filter can be constructedusing the Mitra-Regalia realization.

FIG. 8 shows the effect of magnitude-complementary low-shelf filtersthat may be used in one embodiment of the digital signal processingmethod of the present invention.

FIG. 9 shows a block diagram of an implementation of amagnitude-complementary low-shelf filter that may be used in oneembodiment of the digital signal processing method of the presentinvention.

FIG. 10 shows the static transfer characteristic (the relationshipbetween output and input levels) of a compressor used in one embodimentof the digital signal processing method of the present invention.

FIG. 11 shows a block diagram of a direct form type 1 implementation ofsecond order transfer function used in one embodiment of the digitalsignal processing method of the present invention.

FIG. 12 shows a block diagram of a direct form type 1 implementation ofsecond order transfer function used in one embodiment of the digitalsignal processing method of the present invention.

FIG. 13 is a block diagram of a graphic equalizer used in one embodimentof the digital signal processing method of the present invention.

FIG. 14 is a flow chart for configuring a graphic equalizer with aplurality of filter coefficients in one embodiment of the digital signalprocessing method of the present invention.

FIG. 15 is an exemplary graphical user interface for selecting one ormore profiles to configure the graphic equalizer in one embodiment ofthe digital signal processing method of the present invention.

The figures are not intended to be exhaustive or to limit the inventionto the precise form disclosed. It should be understood that theinvention can be practiced with modification and alteration, and thatthe invention be limited only by the claims and the equivalents thereof.

DETAILED DESCRIPTION

It is to be understood that the present invention is not limited to theparticular methodology, compounds, materials, manufacturing techniques,uses, and applications described herein, as these may vary. It is alsoto be understood that the terminology used herein is used for thepurpose of describing particular embodiments only, and is not intendedto limit the scope of the present invention. It must be noted that asused herein and in the appended embodiments, the singular forms “a,”“an,” and “the” include the plural reference unless the context clearlydictates otherwise. Thus, for example, a reference to “an audio device”is a reference to one or more audio devices and includes equivalentsthereof known to those skilled in the art. Similarly, for anotherexample, a reference to “a step” or “a means” is a reference to one ormore steps or means and may include sub-steps and subservient means. Allconjunctions used are to be understood in the most inclusive sensepossible. Thus, the word “or” should be understood as having thedefinition of a logical “or” rather than that of a logical “exclusiveor” unless the context clearly necessitates otherwise. Language that maybe construed to express approximation should be so understood unless thecontext clearly dictates otherwise.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meanings as commonly understood by one of ordinary skillin the art to which this invention belongs. Preferred methods,techniques, devices, and materials are described, although any methods,techniques, devices, or materials similar or equivalent to thosedescribed herein may be used in the practice or testing of the presentinvention. Structures described herein are to be understood also torefer to functional equivalents of such structures.

1.0 Overview

First, some background on linear time-invarient systems is helpful. Alinear, time-invariant (LTI) discrete-time filter of order N with inputx[k] and output y[k] is described by the following difference equation:

y[k]=b ₀ x[k]+b ₁ x[k−1]+ . . . +b _(N) x[k−N]+a ₁ y[k−1]+a ₂ y[k−2]+ .. . +a _(N) y[k−N]

where the coefficients {b0, b1, . . . , bN, a1, a2, . . . , aN} arechosen so that the filter has the desired characteristics (where theterm desired can refer to time-domain behavior or frequency domainbehavior).

The difference equation above can be excited by an impulse function,δ[k], whose value is given by

${\delta \;\lbrack k\rbrack} = \{ \begin{matrix}{1,{k = 0}} \\{0,{k \neq 0}}\end{matrix} $

When the signal δ[k] is applied to the system described by the abovedifference equation, the result is known as the impulse response, h[k].It is a well-known result from system theory that the impulse responseh[k] alone completely characterizes the behavior of a LTI discrete-timesystem for any input signal. That is, if h[k] is known, the output y[k]for an input signal x[k] can be obtained by an operation known asconvolution. Formally, given h[k] and x[k], the response y[k] can becomputed as

${y\lbrack k\rbrack} = {\sum\limits_{n = 0}^{\infty}{{h\lbrack n\rbrack}{x\lbrack {k - n} \rbrack}}}$

Some background on the z-transform is also helpful. The relationshipbetween the time-domain and the frequency-domain is given by a formulaknown as the z-transform. The z-transform of a system described by theimpulse response h[k] can be defined as the function H(z) where

${H(z)} = {\sum\limits_{k = 0}^{\infty}{{h\lbrack k\rbrack}z^{- k}}}$

and z is a complex variable with both real and imaginary parts. If thecomplex variable is restricted to the unit circle in the complex plane(i.e., the region described by the relationship [z|=1), what results isa complex variable that can be described in radial form as

z=ε ^(jθ), where 0≦θ≦2π and j=√{square root over (−1)}

Some background on the discrete-time fourier transform is alsoinstructive. With z described in radial form, the restriction of thez-transform to the unit circle is known as the discrete-time Fouriertransform (DTFT) and is given by

${H( \in^{j\theta} )} = {\sum\limits_{k = 0}^{\infty}\; {{h\lbrack k\rbrack}^{{- j}\; k\; \theta}}}$

Of particular interest is how the system behaves when it is excited by asinusoid of a given frequency. One of the most significant results fromthe theory of LTI systems is that sinusoids are eigenfunctions of suchsystems. This means that the steady-state response of an LTI system to asinusoid sin(θ0k) is also a sinusoid of the same frequency θ0, differingfrom the input only in amplitude and phase. In fact, the steady-stateoutput, yss[k] of the LTI system when driven by and input x[k]=sin(θ0k)is given by

y _(δδ[k]=A) sin(θ₀ k+φ ₀)

where

A=|H(ε^(jθ) ₀ )|

and

φ₀=arg(H(e ^(jθ) ₀ ))

Finally, some background on frequency response is needed. The equationsabove are significant because indicate that the steady-state response ofan LTI system when driven by a sinusoid is a sinusoid of the samefrequency, scaled by the magnitude of the DTFT at that frequency andoffset in time by the phase of the DTFT at that frequency. For thepurposes of the present invention, what is of concern is the amplitudeof the steady state response, and that the DTFT provides us with therelative magnitude of output-to-input when the LTI system is driven by asinusoid. Because it is well-known that any input signal may beexpressed as a linear combination of sinusoids (the Fourierdecomposition theorem), the DTFT can give the response for arbitraryinput signals. Qualitatively, the DTFT shows how the system responds toa range of input frequencies, with the plot of the magnitude of the DTFTgiving a meaningful measure of how much signal of a given frequency willappear at the system's output. For this reason, the DTFT is commonlyknown as the system's frequency response.

2.0 Digital Signal Processing

FIG. 1 illustrates an example digital signal process flow of a method100 according to one embodiment of the present invention. Referring nowto FIG. 1, method 100 includes the following steps: input gainadjustment 101, first low shelf filter 102, first high shelf filter 103,first compressor 104, second low shelf filter 105, second high shelffilter 106, graphic equalizer 107, second compressor 108, and outputgain adjustment 109.

In one embodiment, digital signal processing method 100 may take asinput audio signal 110, perform steps 101-109, and provide output audiosignal 111 as output. In one embodiment, digital signal processingmethod 100 is executable on a computer chip, such as, withoutlimitation, a digital signal processor, or DSP. In one embodiment, sucha chip may be one part of a larger audio device, such as, withoutlimitation, a radio, MP3 player, game station, cell phone, television,computer, or public address system. In one such embodiment, digitalsignal processing method 100 may be performed on the audio signal beforeit is outputted from the audio device. In one such embodiment, digitalsignal processing method 100 may be performed on the audio signal afterit has passed through the source selector, but before it passes throughthe volume control.

In one embodiment, steps 101-109 may be completed in numerical order,though they may be completed in any other order. In one embodiment,steps 101-109 may exclusively be performed, though in other embodiments,other steps may be performed as well. In one embodiment, each of steps101-109 may be performed, though in other embodiments, one or more ofthe steps may be skipped.

In one embodiment, input gain adjustment 101 provides a desired amountof gain in order to bring input audio signal 110 to a level that willprevent digital overflow at subsequent internal points in digital signalprocessing method 100.

In one embodiment, each of the low-shelf filters 102, 105 is a filterthat has a nominal gain of 0 dB for all frequencies above a certainfrequency termed the corner frequency. For frequencies below the cornerfrequency, the low-shelving filter has a gain of ±G dB, depending onwhether the low-shelving filter is in boost or cut mode, respectively.This is shown in FIG. 2.

FIG. 2 illustrates the effect of a low-shelf filter being implemented byone embodiment of the present invention. Referring now to FIG. 2, thepurpose of a low-shelving filter is to leave all of the frequenciesabove the corner frequency unaltered, while boosting or cutting allfrequencies below the corner frequency by a fixed amount, G dB. Alsonote that the 0 dB point is slightly higher than the desired 1000 Hz. Itis standard to specify a low-shelving filter in cut mode to have aresponse that is at −3 dB at the corner frequency, whereas alow-shelving filter in boost mode is specified such that the response atthe corner frequency is at G−3 dB—namely, 3 dB down from maximum boost.Indeed, all of the textbook formulae for creating shelving filters leadto such responses. This leads to a certain amount of asymmetry, wherefor almost all values of boost or cut G, the cut and boost low-shelvingfilters are not the mirror images of one another. This is something thatneeded to be address by the present invention, and required aninnovative approach to the filters' implementations.

Ignoring for now the asymmetry, the standard method for creating alow-shelving filter is as the weighted sum of highpass and lowpassfilters. For example, let's consider the case of a low-shelving filterin cut mode with a gain of −G dB and a corner frequency of 1000 Hz. FIG.3 shows a highpass filter with a 1000 cutoff frequency and a lowpassfilter with a cutoff frequency of 1000 Hz, scaled by −G dB. Theaggregate effect of these two filters applied in series looks like thelow-shelving filter in FIG. 2. In practice, there are some limitationson the steepness of the transition from no boost or cut to G dB of boostor cut. FIG. 3 illustrates this limitation, with the corner frequencyshown at 1000 Hz and the desired G dB of boost or cut not being achieveduntil a particular frequency below 1000 Hz. It should be noted that allof the shelving filters in the present invention are first-ordershelving filters, which means they can usually be represented by afirst-order rational transfer function:

${H(z)} = \frac{b_{0} + {b_{1}z^{- 1}}}{1 + {a_{1}z^{- 1}}}$

In some embodiments, each of the high-shelf filters 103, 106 is nothingmore than the mirror image of a low-shelving filter. That is, allfrequencies below the corner frequency are left unmodified, whereas thefrequencies above the corner frequency are boosted or cut by G dB. Thesame caveats regarding steepness and asymmetry apply to thehigh-shelving filter. FIG. 4 illustrates the effect of a high-shelffilter implemented by an embodiment of the present invention. Referringnow to FIG. 4, a 1000 Hz high-shelving filter is shown.

FIG. 5 illustrates an example frequency response of a bell filterimplemented by method 100 according to one embodiment of the presentinvention. As shown in FIG. 5, each of the second order filters achievesa bell-shaped boost or cut at a fixed centerfrequency, with F1(z)centered at 30 Hz, F11(z) centered at 16000 Hz, and the other filters inbetween centered at roughly one-octave intervals. Referring to FIG. 5, abell-shaped filter is shown centered at 1000 Hz. The filter has anominal gain of 0 dB for frequencies above and below the centerfrequency, 1000 Hz, a gain of −G dB at 1000 Hz, and a bell-shapedresponse in the region around 1000 Hz.

The shape of the filter is characterized by a single parameter: thequality factor, Q. The quality factor is defined as the ratio of thefilter's center frequency to its 3-dB bandwidth, B, where the 3-dBbandwidth is illustrated as in the figure: the difference in Hz betweenthe two frequencies at which the filter's response crosses the −3 dBpoint.

FIG. 6 illustrates an example graphic equalizer block 600 according toone embodiment of the present invention. Referring now to FIG. 6,graphic equalizer 600 consists of a cascaded bank of eleven second-orderfilters, F₁(z), F₂(z), . . . , F₁₁(z). In one embodiment, graphicequalizer 107 (as shown in FIG. 1) is implemented as graphic equalizer600.

Each of the eleven second-order filters in the present invention can becomputed from formulas that resemble this one:

${F(z)} = \frac{b_{0} + {b_{1}z^{- 1}} + {b_{2}z^{- 2}}}{1 + {a_{1}z^{- 1}} + {a_{2}z^{- 2}}}$

Using such an equation results in one problem: each of the fivecoefficients above, {b₀, b₁, b₂, a₁, a₂} depends directly on the qualityfactor, Q, and the gain, G. This means that for the filter to betunable, that is, to have variable Q and G, all five coefficients mustbe recomputed in real-time. This can be problematic, as suchcalculations could easily consume the memory available to performgraphic equalizer 107 and create problems of excessive delay or fault,which is unacceptable. This problem can be avoided by utilizing theMitra-Regalia Realization.

A very important result from the theory of digital signal processing(DSP) is used to implement the filters used in digital signal processingmethod 100. This result states that a wide variety of filters(particularly the ones used in digital signal processing method 100) canbe decomposed as the weighted sum of an allpass filter and a feedforwardbranch from the input. The importance of this result will become clear.For the time being, suppose that a second-order transfer function, H(z),is being implements to describes a bell filter centered at fc withquality factor Q and sampling frequency Fs by

${H(z)} = \frac{b_{0} + {b_{1}z^{- 1}} + {b_{2}z^{- 2}}}{1 + {a_{1}z^{- 1}} + {a_{2}z^{- 2}}}$

Ancillary quantities k1, k2 can be defined by

$k_{1} = \frac{1 - {\tan ( \frac{\pi \; f_{c}}{{QF}_{s}} )}}{1 + {\tan ( \frac{\pi \; f_{c}}{{QF}_{s}} )}}$k_(z) = −cos (2π f_(c)/F_(s)

and transfer function, A(z) can be defined by

${A(z)} = \frac{k_{2} + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + z^{- 2}}{1 + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + {k_{2}z^{- 2}}}$

A(z) can be verified to be an allpass filter. This means that theamplitude of A(z) is constant for all frequencies, with only the phasechanging as a function of frequency. A(z) can be used as a buildingblock for each bell-shaped filter. The following very important resultcan be shown:

${H(z)} = {{\frac{1}{2}( {1 + G} ){A(z)}} + {\frac{1}{2}( {1 - G} )}}$

This is the crux of the Mitra-Regalia realization. A bell filter withtunable gain can be implemented to show the inclusion of the gain G in avery explicit way. This is illustrated in FIG. 7, which illustrates anexample filter constructed using the Mitra-Regalia realization accordingto one embodiment of the present invention.

There's a very good reason for decomposing the filter in such anon-intuitive manner. Referring to the above equation, remember thatevery one of the a and b coefficients needs to be re-computed whenever Ggets changed (i.e., whenever one of the graphic EQ “slider” is moved).Although the calculations that need to be performed for the a and bcoefficients have not been shown, they are very complex andtime-consuming and it simply isn't practical to recompute them in realtime. However, in a typical graphic EQ, the gain G and quality factor Qremain constant and only G is allowed to vary. This is what makes theequation immediately above so appealing. Notice from the above equationsthat A(z) does not depend in any way on the gain, G and that if Q andthe center-frequency fc remain fixed (as they do in a graphic EQfilter), then k1 and k2 remain fixed regardless of G. Thus, thesevariables only need to be computed once! Computing the gain variable isaccomplished by varying a couple of simple quantities in real time:

$\frac{1}{2}( {1 + G} )$ and$\frac{1}{2}{( {1 + G} ).}$

These are very simple computations and only require a couple of CPUcycles. This leaves only the question of how to implement the allpasstransfer function, A(z), which is a somewhat trivial exercise. Theentire graphic equalizer bank thus consists of 11 cascaded bell filters,each of which is implemented via its own Mitra-Regalia realization:

$\begin{matrix} {F_{1}(z)}arrow  & {{{fixed}\mspace{14mu} k_{1}^{1}},k_{2}^{1},{{variable}\mspace{14mu} G_{1}}} \\ {F_{1}(z)}arrow  & {{{fixed}\mspace{14mu} k_{1}^{2}},k_{2}^{2},{{variable}\mspace{14mu} G_{2}}} \\\vdots & \vdots \\ {F_{11}(z)}arrow  & {{{fixed}\mspace{14mu} k_{1}^{11}},k_{2}^{11},{{variable}\mspace{14mu} G_{11}}}\end{matrix}$

It can be seen from that equation that the entire graphic equalizer bankdepends on a total of 22 fixed coefficients that need to be calculatedonly once and stored in memory. The “tuning” of the graphic equalizer isaccomplished by adjusting the parameters G1, G2, . . . , G11. Refer backto FIG. 6 to see this in schematic form. The Mitra-Regalia realizationwill be used over and over in the implementation of the various filtersused digital signal processing method 100. Mitra-Regalia is also usefulin implementing the shelving filters, where it is even simpler becausethe shelving filters use first-order filter. The net result is that ashelving filter is characterized by a single allpass parameter, k, and again, G. As with the bell filters, the shelving filters are at fixedcorner frequencies (in fact, all of them have 1 kHz as their cornerfrequency) and the bandwidth is also fixed. All told, four shelvingfilters are completely described simply by

H₁(z)→fixed k¹, variable G₁

H₂(z)→fixed k², variable G₂

H₃(z)→fixed k³, variable G₃

H₄(z)→fixed k⁴, variable G₄

As discussed above, there is an asymmetry in the response of aconventional shelving filter when the filter is boosting versus when itis cutting. This is due, as discussed, to the design technique havingdifferent definitions for the 3-dB point when boosting than whencutting. Digital signal processing method 100 relies on the filtersH1(z) and H3(z) being the mirror images of one another and the sameholds for H2(z) and H4(z). This led to the use of a special filterstructure for the boosting shelving filters, one that leads to perfectmagnitude cancellation for H1,H3 and H2,H4, as shown in FIG. 8. Thistype of frequency response is known as magnitude complementary. Thisstructure is unique to the present invention. In general, it is a simplemathematical exercise to derive for any filter H(z) a filter withcomplementary magnitude response. The filter H−1(z) certainly fits thebill, but may not be stable or implementable function of z, in whichcase the solution is merely a mathematical curiosity and is useless inpractice. This is the case with a conventional shelving filter. Theequations above show how to make a bell filter from an allpass filter.These equation applies equally well to constructing a shelving filterbeginning with a first-order allpass filter, A(z), where

${A(z)} = \frac{\alpha - z^{- 1}}{1 - {\alpha \; z^{- 1}}}$

and α is chosen such that

$\alpha = \frac{( {1 - {\sin ( \frac{2\pi \; f_{c}}{F_{s}} )}} )}{\cos ( \frac{2\pi \; f_{c}}{F_{s}} )}$

where fc is the desired corner frequency and Fs is the samplingfrequency. Applying the above equations and re-arranging terms, this canbe expressed as

${H(z)} = {\frac{1 + G}{2}{\{ {1 + {\frac{1 - G}{1 + G}{A(z)}}} \}.}}$

This is the equation for a low-shelving filter. (A high-shelving filtercan be obtained by changing the term (1−G) to (G−1)). Taking the inverseof H(z) results in the following:

$\frac{1}{H(z)} = {\frac{2}{( {1 + G} )( {1 + {\frac{1 - G}{1 + G}{A(z)}}} )}.}$

This equation is problematic because it contains a delay-free loop,which means that it can not be implemented via conventionalstate-variable methods. Fortunately, there are some recent results fromsystem theory that show how to implement rational functions withdelay-free loops. Fontana and Karjalainen show that each step can be“split” in time into two “sub-steps.”

FIG. 9 illustrates an example magnitude-complementary low-shelf filteraccording to one embodiment of the present invention. Refer to FIG. 9,during the first sub-step (labeled “subsample 1”), feed filter A(z) withzero input and compute its output, 10[k]. During this same subsample,calculate the output y[k] using the value of 10[k], which from theequation immediately above can be performed as follows:

$\begin{matrix}{{y\lbrack k\rbrack} = {\frac{1}{1 + {a\frac{1 - G}{1 + G}}}\{ {{\frac{2}{1 + G}{x\lbrack k\rbrack}} + ( {\frac{1 - G}{1 + G}{l_{0}\lbrack k\rbrack}} \}} }} \\{= {\frac{2}{( {1 + G} ) + {a( {1 - G} )}}\{ {{x\lbrack k\rbrack} + {\frac{1 - G}{2}{l_{0}\lbrack k\rbrack}}} \}}}\end{matrix}$

It can be seen from FIG. 9 that these two calculations correspond to thecase where the switches are in the “subsample 1” position. Next, theswitches are thrown to the “subsample 2” position and the only thingleft to do is update the internal state of the filter A(z). Thisunconventional filter structure results in perfect magnitudecomplementarity, 11. This can be exploited for the present invention inthe following manner: when the shelving filters of digital signalprocessing method 100 are in “cut” mode, the following equation can beused:

${H(z)} = {\frac{1 + G}{2}{\{ {1 + {\frac{1 - G}{1 + G}{A(z)}}} \}.}}$

However, when the shelving filters of digital signal processing method100 are in “boost” mode, the following equation can be used with thesame value of G as used in “cut” mode:

$\begin{matrix}{{y\lbrack k\rbrack} = {\frac{1}{1 + {a\frac{1 - G}{1 + G}}}\{ {{\frac{2}{1 + G}{x\lbrack k\rbrack}} + {\frac{1 - G}{{1 + G}\;}{l_{0}\lbrack k\rbrack}}} \}}} \\{= {\frac{2}{( {1 + G} ) + {a( {1 - G} )}}\{ {{x\lbrack k\rbrack} + {\frac{1 - G}{2}{l_{0}\lbrack k\rbrack}}} \}}}\end{matrix}$

This results in shelving filters that are perfect mirror images of onanother, as per FIG. 8, which is what is needed for digital signalprocessing method 100. (Note: Equation 16 can be changed to make ahigh-shelving filter by changing the sign on the (1−G)/2 term). FIG. 8illustrates the effect of a magnitude-complementary low-shelf filterimplemented by an embodiment of the present invention.

Each of the compressors 104, 108 is a dynamic range compressor designedto alter the dynamic range of a signal by reducing the ratio between thesignal's peak level and its average level. A compressor is characterizedby four quantities: the attack time, Tatt, the release time, Trel, thethreshold, KT, and the ratio, r. In brief, the envelope of the signal istracked by an algorithm that gives a rough “outline” of the signal'slevel. Once that level surpasses the threshold, KT, for a period of timeequal to Tart, the compressor decreases the level of the signal by theratio r dB for every dB above KT. Once the envelope of the signal fallsbelow KT for a period equal to the release time, Trel, the compressorstops decreasing the level. FIG. 10 illustrates a static transfercharacteristic (relationship between output and input levels) of acompressor implemented in accordance to one embodiment of the presentinvention.

It is instructive to examine closely the static transfer characteristic.Assume that the signal's level, L[k] at instant k has been somehowcomputed. For instructive purposes, a one single static level, L, willbe considered. If L is below the compressor's trigger threshold, KT, thecompressor does nothing and allows the signal through unchanged. If,however, L is greater than KT, the compressor attenuates the inputsignal by r dB for every dB by which the level L exceeds KT.

It is instructive to consider an instance where L is greater than KT,which means that 20 log₁₀(L)>20 log₁₀(KT). In such an instance, theexcess gain, i.e., the amount in dB by which the level exceeds thethreshold, is: g_(excess)=20 log₁₀(L) −20 log₁₀(KT). As the compressorattenuates the input by r dB for every dB of excess gain, the gainreduction, gR, can be expressed as

${gR} = {\frac{g_{excess}}{R} = {\frac{1}{R} \cdot ( {{20\; {\log_{10}(L)}} - {20\; {\log_{10}( K_{T} )}}} )}}$

From that, it follows that that with the output of the compressor, ygiven by 20 log₁₀(y)=gR*20 log₁₀(x), that the desired output-to-inputrelationship is satisfied.

Conversion of this equation to the linear, as opposed to thelogarithmic, domain yields the following:

$y = {( 10^{\log_{10^{(x)}}} )\frac{1}{R}( {{\log_{10}(L)} - {\log_{10}( K_{T} )}} )}$

Which is equivalent to:

The most important part of the compressor algorithm is determining ameaningful estimate of the signal's level. This is accomplished in afairly straightforward way: a running “integration” of the signal'sabsolute value is kept, where the rate at which the level is integratedis determined by the desired attack time. When the instantaneous levelof the signal drops below the present integrated level, the integratedlevel is allowed to drop at a rate determined by the release time. Givenattack and release times Tatt and Trel, the equation used to keep trackof the level, L[k] is given by

${L\lbrack k\rbrack} = \{ {{\begin{matrix}{( {1 - \alpha_{att}} ){{x\lbrack k\rbrack} + {\alpha_{att}{L\lbrack {k - 1} \rbrack}}}} & {{{for}\mspace{14mu} {{x\lbrack k\rbrack}}} \geq {L\lbrack {k - 1} \rbrack}} \\{( {1 - \alpha_{rel}} ){{x\lbrack k\rbrack} + {\alpha_{rel}{L\lbrack {k - 1} \rbrack}}}} & {{{for}\mspace{14mu} {{x\lbrack k\rbrack}}} < {L\lbrack {k - 1} \rbrack}}\end{matrix}{where}\alpha_{att}} = {{{\exp ( \frac{1}{F_{g}T_{att}} )}{and}\alpha_{rel}} = {\exp ( \frac{1}{5F_{g}T_{rel}} )}}} $

At every point of the level calculation as described above, L[k] ascomputed is compared to the threshold KT, and if L[k] is greater thanKT, the input signal, x[k], is scaled by an amount that is proportionalto the amount by which the level exceeds the threshold. The constant ofproportionality is equal to the compressor ratio, r. After a great dealof mathematical manipulation, \the following relationship between theinput and the output of the compressor is established:

With the level L[k] as computed in Equation 18, the quantity Gexcess byis computed as

G _(excess) =L[k]K _(T) ⁻¹,

which represents the amount of excess gain. If the excess gain is lessthan one, the input signal is not changed and passed through to theoutput. In the event that the excess gain exceeds one, the gainreduction, GR is computed by:

$G_{R} = {( G_{excess} )^{\frac{1 - r}{r}} = ( {{L\lbrack k\rbrack}K_{T}^{- 1}} )^{\frac{1 - r}{r}}}$

and then the input signal is scaled by GR and sent to the output:

output[k]=G_(R) x[k].

Through this procedure, an output signal whose level increases by 1/r dBfor every 1 dB increase in the input signal's level is created.

In practice, computing the inverse K_(T) ⁻¹ for the above equations canbe time consuming, as certain computer chips are very bad at division inreal-time. As KT is known in advance and it only changes when the userchanges it, a pre-computed table of K_(T) ⁻¹ values can be stored inmemory and used as needed. Similarly, the exponentiation operation inthe above equation calculating GR is extremely difficult to perform inreal time, so pre-computed values can be used as an approximation. Sincequantity GR is only of concern when Gexcess is greater than unity, alist of, say, 100 values of GR, pre-computed at integer values of GRfrom GR=1 to GR=100 can be created for every possible value of ratio r.For non-integer values of GR (almost all of them), the quantity in theabove equation calculating GR can be approximated in the following way.Let interp be the amount by which Gexcess exceeds the nearest integralvalue of Gexcess. In other words,

interp=G _(excess)−└(G _(excess))┘

and let GR,0 and GR,1 refer to the pre-computed values

$G_{R,0} = \lfloor ( G_{excess} ) \rfloor^{\frac{1 - r}{r}}$and$G_{R,1} = {\lfloor ( {1 + G_{{excess}\;}} ) \rfloor^{\frac{1 - r}{r}}.}$

Linear interpolation may then be used to compute an approximation of GRas follows:

G _(R) ≈G _(R,0) interp*(G _(R,1) −G _(R,0))

The error between the true value of GR and the approximation in theabove equation can be shown to be insignificant for the purposes of thepresent invention. Furthermore, the computation of the approximate valueof GR requires only a few arithmetic cycles and several reads frompre-computed tables. In one embodiment, tables for six different valuesof ratio, r, and for 100 integral points of Gexcess may be stored inmemory. In such an embodiment, the entire memory usage is only 600 wordsof memory, which can be much more palatable than the many hundred cyclesof computation that would be necessary to calculate the true value of GRdirectly. This is a major advantage of the present invention.

Each of the digital filters in digital signal processing method 100 maybe implemented using any one a variety of potential architectures orrealizations, each of which has its trade-offs in terms of complexity,speed of throughput, coefficient sensitivity, stability, fixedpointbehavior, and other numerical considerations. In a specific embodiment,a simple architecture known as a direct-form architecture of type 1(DF1) may be used. The DF1 architecture has a number of desirableproperties, not the least of which is its clear correspondence to thedifference equation and the transfer function of the filter in question.All of the digital filters in digital signal processing method 100 areof either first or second order.

The second-order filter will be examined in detail first. As discussedabove, the transfer function implemented in the second-order filter isgiven by

${{H(z)} = \frac{b_{0} + {b_{1}z^{- 1}} + {b_{2}z^{- 2}}}{1 + {a_{1}z^{- 1}} + {a_{2}z^{- 2}}}},$

which corresponds to the difference equation

y[k]=b ₀ x[k]+b ₁ x[k−1]+b ₂ x[k−2]−a ₁ y[k−1]−a ₂ y[k−2].

FIG. 11 illustrates the DF1 architecture for a second-order filteraccording to one embodiment of the present invention. As shown in FIG.11, the multiplier coefficients in this filter structure correspond tothe coefficients in the transfer function and in the difference equationabove. The blocks marked with the symbol z−1 are delay registers, theoutputs of which are required at every step of the computation. Theoutputs of these registers are termed state variables and memory isallocated for them in some embodiments of digital signal processingmethod 100. The output of the digital filter is computed as follows:

-   -   Initially, every one of the state variables is set to zero. In        other words,

x[−1]=x[−2]=y[−1]=y[−2]=0.

-   -   At time k=0 the following computation is done, according to FIG.        11:

y[0]=b ₀ x[0]+b ₁ x[−1]+b ₂ x[−2]−a ₁ y[−1]−α₂ y[−2].

-   -   Then, the registers are then updated so that the register marked        by x[k−1] now holds x[0], the register marked by x[k−2] now        holds x[−1], the register marked by y[k−1] holds y[0], and the        register marked by y[k−2] holds y[−1].    -   At time k=1 the following computation is done:

y[1]=b ₀ x[1]+b ₁ x[0]+b ₂ x[−1]−a ₁ y[0]−a ₂ y[−1]

-   -   Then, the register update is again completed so that the        register marked by x[k−1] now holds x[1], the register marked by        x[k−2] now holds x[0], the register marked by y[k−1] holds y[1],        and the register marked by y[k−2] holds y[0].    -   This process is then repeated over and over for all instants k:        A new input, x[k], is brought in, a new output y[k] is computed,        and the state variables are updated.

In general, then, the digital filtering operation can be viewed as a setof multiplications and additions performed on a data stream x[0], x[1],x[2], . . . using the coefficients b0, b1, b2, a1, a2 and the statevariables x[k−1], x[k−2], y[k−1], y[k−2].

The manifestation of this in specific situations is instructive.Examination of the bell filter that constitutes the fundamentalbuilding-block of graphic equalizer 107 is helpful. As discussed above,the bell filter is implemented with a sampling frequency Fs, gain G at acenter frequency fc, and quality factor Q as

${H(z)} = {{\frac{1}{2}( {1 + G} ){A(z)}} + {\frac{1}{2}( {1 - G} )}}$

where A(z) is an allpass filter defined by

${A(z)} = \frac{k_{2} + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + z^{- 2}}{1 + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + {k_{2}z^{- 2}}}$

where k1 and k2 are computed from fc and Q via the equations

$k_{1} = \frac{1 - {\tan ( \frac{\pi \; f_{c}}{{QF}_{s}} )}}{1 + {\tan ( \frac{\pi \; f_{c}}{{QF}_{s}} )}}$and k_(z) = −cos (2π f_(c)/F_(s)

The values k1 and k2 are pre-computed and stored in a table in memory.To implement a filter for specific values of Q and fc, the correspondingvalues of k1 and k2 are looked up in this table. Since there are elevenspecific values of fc and sixteen specific values of Q in the algorithm,and the filter operates at a single sampling frequency, Fs, and only k2depends on both fc and Q, the overall storage requirements for the k1and k2 coefficient set is quite small (11×16×2 words at worst).

Observe from the equation above for A(z) that its coefficients aresymmetric. That is, the equations can be re-written as

${A(z)} = \frac{z^{- 2} + {geq\_ blz}^{- 1} + {geq\_ b0}}{1 + {geq\_ blz}^{- 1} + {geq\_ b0z}^{- 2}}$where geq_b0 = k₂ and geq_b1 = k₁(1 + k₂).

Observe that A(z) as given in the above equation implies the differenceequation

y[k]=geq _(—) b0(x[k]+geq _(—) b1x[k−1]+x[k−2]−geq _(—) b1y[k−1]−geq_(—) b0y[k−2],

which can be rearranged to yield

y[k]=geq _(—) b0(x[k]−y[k−2])+geq _(—) b1(x[k−1]−y[k−1])+x[k−2]

In a specific embodiment, the state variables may be stored in arraysxv[ ] and yv[ ] with xv[0] corresponding to x[k−2], xv[1] correspondingto x[k−1], yv[0] corresponding to y[k−2] and yv[1] corresponding toy[k−1]. Then the following code-snippet implements a single step of theallpass filter:

void allpass(float *xv, float *yv, float *input, float *output) {  *output = geq_b0 * (*input − yv[0]) + geq_b1 *   (xv[1] − yv[1]) +xv[0]   xv[0] = xv[1]; \\ update   xv[1] = *input; \\ update   yv[0] =yv[1]; \\update   yv[1] = *output; \\update }

Now the loop must be incorporated around the allpass filter as per theequations above. This is trivially realized by the following:

void bell(float *xv, float *yv, float gain, float *input, float *output){   allpass(xv, yv, input, output);   *output = 0.5 * (1.0−gain) *(*output) + 0.5 * (1.0+gain) * (*input); }

More concisely, the previous two code snippets can be combined into asingle routine that looks like this:

void bell(float *xv, float *yv, float gain, float *input, float *output){   float ap_output = geq_b0 * (*input − yv[0]) +   geq_b1 * (xv[1] −yv[1]) + xv[0]   xv[0] = xv[1]; \\ update   xv[1] = *input; \\ update  yv[0] = yv[1]; \\update   yv[1] = *output; \\update   *output = 0.5 *(1.0−gain) * ap_output + 0.5 * (1.0+gain) * (*input); }

The first-order filter will now be examined in detail. These filters canbe described by the transfer function

${{H(z)} = \frac{b_{0} + {b_{1}z^{- 1}}}{1 + {a_{1}z^{- 1}}}},$

which corresponds to the difference equation

y[k]=b ₀ x[k]+b ₁ x[k−1]−a ₁ y[k−1].

FIG. 12 illustrates the DF1 architecture for a first-order filteraccording to one embodiment of the present invention. Referring now toFIG. 12, the multiplier coefficients in this filter structure correspondin a clear way to the coefficients in the transfer function and in thedifference equation. The output of the digital filter is computed asfollows:

-   -   Initially, every one of the state variables is set to zero. In        other words,

x[−1]=y[−1]=0.

-   -   At time k=0 the following computation is done, according to FIG.        11:

y[0]=b ₀ x[0]+b ₁ x[−1]−a ₁ y[−1].

-   -   Then, the registers are then updated so that the register marked        by x[k−1] now holds x[0], and the register marked by y[k−1]        holds y[0].    -   At time k=1 the following computation is done:

y[1]=b ₀ x[1]+b ₁ x[0]−a ₁ y[0]

-   -   Then, the register update is again completed so that the        register marked by x[k−1] now holds x[1] and the register marked        by y[k−1] holds y[1].    -   This process is then repeated over and over for all instants k:        A new input, x[k], is brought in, a new output y[k] is computed,        and the state variables are updated.

In general, then, the digital filtering operation can be viewed as a setof multiplications and additions performed on a data stream x[0], x[1],x[2], . . . using the coefficients b0, b1, a1 and the state variablesx[k−1], y[k−1].

FIG. 13 is a block diagram of a graphic equalizer 1300 used in oneembodiment of the digital signal processing method of the presentinvention. In various embodiments, a profile may comprise a plurality offilter equalizing coefficients which may be used to configure thegraphic equalizer 1300. As discussed herein, once configured by theplurality of filter equalizing coefficients (e.g., coefficientmodifiers), the graphic equalizer 1300 may equalize a plurality ofsignals. Although adjustments to the filters of the graphic equalizer1300 may be performed (e.g., using a desired gain value), the filtersmay not need to be reconfigured with a different set of filterequalizing coefficients while equalizing a plurality of signals.

In various embodiments, the graphic equalizer 1300 comprises a filtermodule 1302, a profile module 1304, and an equalizing module 1306. Thegraphic equalizer 1300 may comprise the 11-band graphic equalizer 107.Those skilled in the art will appreciate that the graphic equalizer 1300may comprise any number of bands.

The filter module 1302 comprises any number of filters. In variousembodiments, the filters of the plurality of the filters in the filtermodule 1302 are in parallel with each other. One or more of the filtersof the plurality of filters may be configured to filter a signal at adifferent frequency. In some embodiments, the filters of the pluralityof filters are second order bell filters.

The profile module 1304 is configured to receive a profile. A profilecomprises a plurality of filter equalizing coefficients (e.g., filterequalizing coefficient modifiers) which may be used to configure thefilters of the graphic equalizer (e.g., the filters of the plurality offilters in the filter module 1302). In some embodiments, a profile maybe directed to a particular type or model of hardware (e.g., speaker),particular listening environment (e.g., noisy or quiet), and/or audiocontent (e.g., voice, music, or movie). In some examples of hardwareprofiles, there may be a profile directed to cellular telephones, wiredtelephones, cordless telephones, communication devices (e.g., walkietalkies and other two-way radio transceivers), police radios, musicplayers (e.g., Apple IPod and Microsoft Zune), headsets, earpieces,microphones, and/or the like.

For example, when a profile is directed to a particular type or model ofhardware, the plurality of filter equalizing coefficients of thatprofile may configure the graphic equalizer 1300 to equalize one or moresignals as to improve quality for that particular type or model ofhardware. In one example, a user may select a profile directed at aparticular model of PC speakers. The plurality of filter equalizingcoefficients of the selected profile may be used to configure thegraphic equalizer 1300 to equalize signals that are to be played throughthe PC speaker such that the perceived quality of the sound through thePC speaker attains a quality that may be higher than if the graphicequalizer 1300 was not so configured.

In another example, the user may select a profile directed to aparticular model of microphone. The plurality of filter equalizingcoefficients of the selected profile may be used to configure thegraphic equalizer 1300 to equalize signals that are received from themicrophone such that the perceived quality of the sound may be enhanced.

There may also be profiles directed to one or more listeningenvironments. For example, there may be a profile directed to clarifythe sound of a voice during a telephone conversation, to clarify voiceor music in high noise environments, and/or to clarify voice or musicenvironments where the listener is hearing impaired. There may also beseparate profiles for different audio content including a profile forsignals associated with voice, music, and movies. In one example, theremay be different profiles for different types of music (e.g.,alternative music, jazz, or classical).

Those skilled in the art will appreciate that the enhancement orclarification of sound may refer to an improved perception of the sound.In various embodiments, the filter equalizing coefficients of theprofile may be selected as to improve the perception of sound for aparticular device playing a particular audio content (e.g., a movie overa portable media player). The filter equalizing coefficients of theplurality of filter equalizing coefficients in the profile may beselected and/or generated based on a desired sound output and/orquality.

The equalizing module 1306 may configure the filters of the filtermodule 1302 using the coefficients of the plurality of filter equalizingcoefficients in the profile. As discussed herein, the filters of thegraphic equalizer 1300 may be implemented via a Mitra-Regaliarealization. In one example, once the equalizing module 1306 configuresthe filters with the filter equalizing coefficients, the coefficients ofthe filters may remain fixed (i.e., the filters are not reconfiguredwith new coefficients before, during, or after equalizing multiplesignals). Although the filters of the graphic equalizer 1300 may not bereconfigured with new filter equalizing coefficients, the filters may beperiodically adjusted with a gain value (e.g., the gain variable).Computing the gain value to further configure the equalizer filters maybe accomplished by varying simple quantities as previously discussed.

The equalizing module 1306 may also equalize multiple signals using thefilters configured by the filter equalizing coefficients of the profile.In one example, the equalizing module 1306 equalizes a first signalcontaining multiple frequencies using the previously configuredequalizer filters of the filter module 1306. A second signal may also besimilarly equalized using the equalizer filters as previously configuredby the filter equalizing coefficients. In some embodiments, theequalizing module 1306 adjusts the gain to further configure theequalizer filters before the second signal is equalized.

In some embodiments, the profile may comprise one or more shelf filtercoefficients. As discussed herein, one or more shelf filters maycomprise first order filters. The one or more shelf filters (e.g., lowshelf 1 102, high shelf 1 103, low shelf 2 105, and high shelf 2 106 ofFIG. 1) may be configured by the shelf filter coefficient(s) within theprofile. In one example, the profile may be directed to a particularbuilt-in speaker of a particular model of computer. In this example,shelf filter coefficients within the profile may be used to configurethe shelf filters to improve or enhance sound quality from the built-inspeaker. Those skilled in the art will appreciate that the profile maycomprise many different filter coefficients that may be used toconfigure any filter to improve or enhance sound quality. The shelffilters or any filter may be further configured with the gain value asdiscussed herein.

Those skilled in the art will appreciate that more or less modules mayperform the functions of the modules described in FIG. 13. There may beany number of modules. Modules may comprise hardware, software, or acombination of both. Hardware modules may comprise any form of hardwareincluding circuitry. In some embodiments, filter circuitry performs thesame or similar functions as the filter module 1302. Profile circuitrymay perform the same or similar functions as the profile module 1304 andequalizing circuitry may perform the same or similar functions as theequalizing module 1306. Software modules may comprise instructions thatmay be stored within a computer readable medium such as a hard drive,RAM, flash memory, CD, DVD, or the like. The instructions of thesoftware may be executable by a processor to perform a method.

FIG. 14 is a flow chart for configuring a graphic equalizer 1300 with aplurality of filter equalizing coefficients in one embodiment of thedigital signal processing method of the present invention. In step 1402,the profile module 1304 receives a profile with a plurality of filterequalizing coefficients. In various embodiments, a user of a digitaldevice may select a profile that is associated with available hardware,listening environment, and/or audio content. A digital device is anydevice with memory and a processor. In some examples, a digital devicemay comprise a cellular telephone, a corded telephone, a wirelesstelephone, a music player, media player, a personal digital assistant,e-book reader, laptop, desk computer or the like.

The profile may be previously stored on the digital device (e.g., withina hard drive, Flash memory, or RAM), retrieved from firmware, ordownloaded from a communication network (e.g., the Internet). In someembodiments, different profiles may be available for download. Eachprofile may be directed to a particular hardware (e.g., model and/ortype of speaker or headphone), listening environment (e.g., noisy),and/or audio content (e.g., voice, music, or movies). In one example,one or more profiles may be downloaded from a manufacturer and/or awebsite.

In step 1404, the equalizing module 1306 configures filters of thegraphic equalizer 1300 (e.g., equalizer filters of the filter module1302) with the plurality of filter equalizing coefficients from theprofile. The equalizing module 1306 or another module may also configureone or more other filters with other coefficients contained within theprofile.

In step 1406, the equalizing module 1306 receives a first signal. Thefirst signal may comprise a plurality of frequencies to be equalized bythe preconfigured equalizer filters of the filter module 1302.

In step 1408, the equalizing module 1306 adjusts filters of the graphicequalizer 1300 (e.g., the filters of the filter module 1302) using afirst gain (e.g., a first gain value). In some embodiments, the gain isassociated with a speaker. The gain may be associated with the desiredcharacteristic of the sound to be stored. Further, the gain may beassociated with the first signal. In some embodiments, the equalizingmodule 1306 adjusts of the filter module 1302 prior to receiving thefirst signal.

In step 1410, the equalizing module 1306 equalizes the first signal. Invarious embodiments, the equalizing module 1306 equalizes the firstsignal with the equalizer filters of the filter module 1302 that wasconfigured by the filter equalizing coefficients of the profile andfurther adjusted by the gain.

The equalizing module 1306 may output the first signal in step 1412. Insome embodiments, the first signal may be output to a speaker device orstorage device. In other embodiments, the first signal may be output forfurther processing (e.g., by one or more compressors and/or one or morefilters).

In step 1414, the equalizing module 1306 receives the second signal. Instep 1416, the equalizing module 1306 adjusts filters of the graphicequalizer 1300 with a second gain. In one example, the equalizing module1306 further adjusts the filters of the filter module 1302 that werepreviously configured using the filter equalizing coefficients. Thesecond gain may be associated with the first signal, the second signal,a speaker, or a sound characteristic. In some embodiments, this step isoptional.

In step 1418, the equalizing module 1306 equalizes the second signalwith the graphic equalizer 1300. In various embodiments, the equalizingmodule 1306 equalizes the second signal with the equalizer filters ofthe filter module 1302 that was configured by the filter equalizingcoefficients of the profile and further adjusted by the first and/orsecond gain. The equalizing module 1306 may output the second signal instep 1420.

Those skilled in the art will appreciate that different profiles may beapplied during signal processing (e.g., while sound is playing through aspeaker). In some embodiments, a user may select a first profilecontaining filter equalizing coefficients which are used to configurethe graphic equalizer 1300 during processing. The change or enhancementcaused by the signal processing of the configured graphic equalizer 1300may be perceptible by a listener. The user may also select a secondprofile containing different filter equalizing coefficients which areused to reconfigure the graphic equalizer 1300. As discussed herein, thechange or enhancement caused by the signal processing of thereconfigured graphic equalizer 1300 may also be perceptible by thelistener. In various embodiments, a listener (e.g., user) may select avariety of different profiles during signal processing and listen to thedifferences. As a result, the listener may settle on a preferredprofile.

FIG. 15 is an exemplary graphical user interface 1500 for selecting oneor more profiles to configure the graphic equalizer in one embodiment ofthe digital signal processing method of the present invention. Invarious embodiments, the graphical user interface 1500 may be displayedon a monitor, screen, or display on any digital device. The graphicaluser interface 1500 may be displayed using any operating system (e.g.,Apple OS, Microsoft Windows, or Linux). The graphical user interface1500 may also be displayed by one or more applications such as AppleItunes.

The graphical user interface 1500 is optional. Various embodiments maybe performed on a variety of hardware and software platforms that may ormay not use a graphical user interface. In one example, some embodimentsmay be performed on a RIM Blackberry communication device. In anotherexample, some embodiments may be performed on an application on acomputer such as Apple Itunes.

For example, an existing media player or application may be configured(e.g., by downloading a plug-in or other software) to receive theprofile and apply the filter equalizing coefficients to a graphicequalizer. In one example, a plug-in for Apple Itunes is downloaded andinstalled. The user may select music to play. The music signals may beintercepted from Apple Itunes and processed using one or more filtersand a graphic equalizer configured by one or more profiles (optionallyselected by the user). The processed signals may then be passed back tothe application and/or operating system to continue processing or tooutput to a speaker. The plug-in may be downloaded and/or decryptedbefore installing. The profile may also be encrypted. The profile, insome embodiments, may comprise a text file. The application may allowthe user the option to minimize the application and display thegraphical user interface 1500.

In some embodiments, the graphical user interface 1500 displays avirtual media player and a means for the user to select one or moreprofiles. The on/off button 1502 may activate the virtual media player.

The built-in speaker button 1504, the desktop speaker button 1506, andthe headphones button 1508 may each be selectively activated by the userthrough the graphical user interface 1500. When the user selectivelyactivates the button 1504, the desktop speaker button 1506, or theheadphones button 1508, an associated profile may be retrieved (e.g.,from local storage such as a hard drive or firmware) or downloaded(e.g., from a communication network). The filter equalizing coefficientsof the plurality of coefficients may then be used to configure a graphicequalizer to modify sound output. In one example, the profile associatedwith the headphones button 1508 comprises filter equalizing coefficientsconfigured to adjust, modify, enhance or otherwise alter output ofheadphones that may be operatively coupled to the digital device.

The music button 1510 and the movie button 1512 may each be selectivelyactivated by the user through the graphical user interface 1500. Similarto the built-in speaker button 1504, the desktop speaker button 1506,and the headphones button 1508, when the user selectively activates themusic button 1510 or the movie button 1512, an associated profile may beretrieved. In some embodiments, the associated profile comprises filterequalizing coefficients that may be used to configure the filters of thegraphic equalizer as to adjust, modify, enhance, or otherwise altersound output.

It will be appreciated by those skilled in the art that multipleprofiles may be downloaded and one or more of the filter equalizingcoefficients of one profile may work with the filter equalizingcoefficients of another profile to improve sound output. For example,the user may select the built-in speaker button 1504 which configuresthe filters of the graphic equalizer with filter equalizing coefficientsfrom a first profile in order to improve sound output from the built-inspeaker. The user may also select the music button 1510 which furtherconfigures the filter equalizing coefficients of the graphic equalizerwith filter equalizing coefficients from a second profile in order tofurther improve the sound output of music from the built-in speaker.

In some embodiments, multiple profiles are not combined. For example,the user may select the built-in speaker button 1504 and the musicbutton 1510 which retrieves a single profile comprising filterequalizing coefficients to improve or enhance the sound output of themusic from the built-in speaker. Similarly, there may be a separateprofile that is retrieved when the user activates the desktop speakerbutton 1506 and the music button 1510. Those skilled in the art willappreciate that there may be any number of profiles associated with oneor more user selections of hardware, listening environment, and/or mediatype.

The rewind button 1514, the play button 1516, the forward button 1518,and the status display 1520 may depict functions of the virtual mediaplayer. In one example, after the user has selected the profiles to beused (e.g., through selecting the buttons discussed herein), the usermay play a media file (e.g., music and/or a movie) through the playbutton 1516. Similarly, the user may rewind the media file using therewind button 1514 and fast forward the media file using the fastforward button 1518. The status display 1520 may display the name of themedia file to the user, as well as associated information about themedia file (e.g., artist, total duration of media file, and duration ofmedia file left to play). The status display 1520 may display anyinformation, animation, or graphics to the user.

In various embodiments, a plug-in or application for performing one ormore embodiments described herein must be registered before the plug-inor application is fully functional. In one example, a free trial may bedownloadable by a user. The trial version may play a predeterminedperiod of time (e.g., 1 minute) of enhanced sound or audio beforereturning the signal processing to the previous state (e.g., the soundmay return to a state before the trial program was downloaded). In someembodiments, the unenhanced sound or audio may be played for anotherpredetermined period (e.g., 1 or 2 minutes) and the signal processingmay again return to enhancing the sound quality using the previouslyconfigured graphic equalizer and/or other filters. This process may goback and forth through the duration of the song. Once the registrationof the plug-in or application is complete, the plug-in or applicationmay be configured to process signals without switching back and forth.

Referring back to the equations above, a first-order shelving filter canbe created by applying the equation

${A(z)} = \frac{k_{2} + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + z^{- 2}}{1 + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + {k_{2}z^{- 2}}}$

to the first-order allpass filter A(z), where

${A(z)} = \frac{\alpha - z^{- 1}}{1 - {\alpha z}^{- 1}}$

where α is chosen such that

$\alpha = \frac{( {1 - {\sin ( \frac{2\pi \; f_{c}}{F_{s}} )}} )}{\cos ( \frac{2\pi \; f_{c}}{F_{s}} )}$

where fc is the desired corner frequency and Fs is the samplingfrequency. The allpass filter A(z) above corresponds to the differenceequation

y[k]=αx[k]−x[k−1]+αy[k−1].

If allpass coefficient α is referred to as allpass coef and the equationterms are rearranged, the above equation becomes

y[k]=allpass_coef(x[k]+y[k−1])−x[k−1].

This difference equation corresponds to a code implementation of ashelving filter that is detailed below.

One specific software implementation of digital signal processing method100 will now be detailed.

Input gain adjustment 101 and output gain adjustment 109, describedabove, may both be accomplished by utilizing a “scale” function,implemented as follows:

void scale(gain, float *input, float *output) {   for (i = 0; i <NSAMPLES; i++)   {     *output++ = inputGain * (*input++);   } }

First low shelf filter 102 and second low shelf filter 105, describedabove, may both be accomplished by utilizing a “low_shelf” function,implemented as follows:

void low_shelf(float *xv, float *yv, float *wpt, float *input, float*output) {   float l;   int i;   for (i = 0; i < NSAMPLES; i++)   {    if (wpt[2] < 0.0) \\ cut mode, use conventional realization     { \\allpass_coef = alpha       yv[0] = ap_coef * (*input) + (ap_coef *      ap_coef − 1.0) * xv[0];       xv[0] = ap_coef * xv[0] + *input;      *output++ = 0.5 * ((1.0 + wpt[0]) * (*input++) +       (1.0 −wpt[0]) * yv[0]);     }     else \\ boost mode, use special realization    {       1 = (ap_coef * ap_coef − 1.0) * xv[0];       *output =wpt[1] * ((*input++) − 0.5 * (1.0 − wpt[0]) * 1);       xv[0] =ap_coef * xv[0] + *output++;     }   } }

As this function is somewhat complicated, a detailed explanation of itis proper. First, the function declaration provides:

void low_shelf(float*xv, float*yv, float*wpt, float*input, float*output)

The “low_shelf” function takes as parameters pointers to five differentfloating-point arrays. The arrays xv and yv contain the “x” and “y”state variables for the filter. Because the shelving filters are allfirst-order filters, the state-variable arrays are only of length one.There are distinct “x” and “y” state variables for each shelving filterused in digital signal processing method 100. The next array used is thearray of filter coefficients “wpt” that pertain to the particularshelving filter. wpt is of length three, where the elements wpt[0],wpt[1], and wpt[2] describe the following:

wpt[0]=G

wpt[1]=2[(1+G)+α(1−G)]⁻¹

wpt[2]=−1 when cutting, 1 when boosting

and α is the allpass coefficient and G is the shelving filter gain. Thevalue of αis the same for all shelving filters because it is determinedsolely by the corner frequency (it should be noted that and all four ofthe shelving filters in digital signal processing method 100 have acorner frequency of 1 kHz). The value of G is different for each of thefour shelving filters.

The array “input” is a block of input samples that are fed as input toeach shelving filter, and the results of the filtering operation arestored in the “output” array.

The next two lines of code,

float 1;

int i;

allocate space for a loop counter variable, i, and an auxiliaryquantity, 1, which is the quantity 10[k] from FIG. 9.

The next line of code,

for (i=0; i<NS AMPLES; i++)

performs the code that follows a total of NSAMPLES times, where NSAMPLESis the length of the block of data used in digital signal processingmethod 100.

This is followed by the conditional test

if (wpt[2]<0.0)

and, recalling the equations discussed above, wpt[2]<0 corresponds to ashelving filter that is in “cut” mode, whereas wpt[2]>=0 corresponds toa shelving filter that is in “boost” mode. If the shelving filter is incut mode the following code is performed:

if (wpt [2] < 0.0) \\ cut mode, use conventional realization {  \\allpass_coef = alpha    yv[0] = ap_coef * (*input) + (ap_coef * ap_coef− 1.0) * xv [0];    xv[0] = ap_coef * xv [0] + *input;    *output++ =0.5 * ((1.0 + wpt [0]) * (*input++) +   (1.0 − wpt [0]) * yv [0]); }The value xv[0] is simply the state variable x[k] and yv[0] is justyv[k]. The code above is merely an implementation of the equations

y[k]=α·in[k]+(α²−1)·x[k]

x[k]=α·x[k]+in[k]

out[k]= 1/2((1+G)·in[k]+(1−G)·y[k])

If the shelving filter is in cut mode the following code is performed:

else \\ boost mode, use special realization {   1 = (ap_coef * ap_coef −1.0) * xv [0];   *output = wpt [1] * ((*input++) − 0.5 * (1.0 − wpt[0]) * 1);   xv[0] = ap_coef * xv [0] + *output++; }which implements the equations

i ₀ [k]=(α²−1)·x[k]

out[k]=2[(1+G)+α(1−G)]⁻¹·(in[k]−½(1−G)i ₀ [k])

x[k]=α·x[k−1]+out[k]

First high shelf filter 103 and second high shelf filter 106, describedabove, may both be accomplished by utilizing a “high_shelf” function,implemented as follows:

void high_shelf(float *xv, float *yv, float *wpt, float *input, float*output) {   float l;   int i;   for (i = 0; i < NSAMPLES; i++)   {    if (wpt[2] < 0.0) \\ cut mode, use conventional realization,     {\\ allpass_coef = alpha       yv[0] = allpass_coef * (*input) +(allpass_coef *       allpass_coef − 1.0) *     xv[0];       xv[0] =allpass_coef * xv[0] + *input;       *output++ = 0.5 * ((1.0 + wpt[0]) *(*input++) −       (1.0 − wpt[0]) * yv[0]);     }     else \\ boostmode, use special realization     {       l = (allpass_coef *allpass_coef − 1.0) * xv[0];       *output = wpt[1] * ((*input++) +0.5 * (1.0 − wpt[0]) * l);       xv[0] = allpass_coef * xv[0] +*output++;     }   } }

Implementing the high-shelving filter is really no different thanimplementing the low-shelving filter. Comparing the two functions above,the only substantive difference is in the sign of a single coefficient.Therefore, the program flow is identical.

Graphic equalizer 107, described above, may be implemented using aseries of eleven calls to a “bell” filter function, implemented asfollows:

void bell(float *xv, float *yv, float *wpt, float *input, float *output){   float geq_gain = wpt[0]; \\ G   float geq_b0 = wpt[1]; \\ k2   floatgeq_b1 = wpt[2]; \\ k1(1+k2)   float ap_output;   int i;   for (i = 0; i< NSAMPLES; i++)   {     ap_output = geq_b0 * (*input − yv[0]) +geq_b1 *     (xv[1] − yv[1]) + xv[0];     xv[0] = xv[1]; \\ update    xv[1] = *input; \\ update     yv[0] = yv[1]; \\update     yv[1] =*output; \\update     *output++ = 0.5 * (1.0−gain) * ap_output + 0.5 *    (1.0+gain) * (*input++);   } }

The function bell( ) takes as arguments pointers to arrays xv (the “x”state variables), yv (the “y” state variables), wpt (which contains thethree graphic EQ parameters G, k2, and k1(1+k2)), a block of inputsamples “input”, and a place to store the output samples. The first fourstatements in the above code snippet are simple assignment statementsand need no explanation.

The for loop is executed NSAMPLES times, where NSAMPLES is the size ofthe block of input data. The next statement does the following:

ap_output = geq_b0 * (*input − yv[0]) + geq_b1 * (xv[1] − yv[1]) + xv[0]

The above statement computes the output of the allpass filter asdescribed above. The next four statements do the following:

xv[0]=xv[1];

shifts the value stored in x[k−1] to x[k−2].

xv[1]=*input;

shifts the value of input[k] to x[k−1].

yv[0]=yv[1];

shifts the value stored in y[k−1] to y[k−2].

yv[1]=*output;

shifts the value of output[k], the output of the allpass filter, toy[k−1].

Finally, the output of the bell filter is computed as

*output++=0.5*(1.0-gain)*ap_output+0.5*(1.0+gain)*(*input++);

First compressor 104 and second compressor 108, described above, may beimplemented using a “compressor” function, implemented as follows:

void compressor(float *input, float *output, float *wpt, int index) {  static float level;   float interp, GR, excessGain, L, invT, ftempabs;  invT = wpt[2];   int i, j;   for (i = 0; i < NSAMPLES; i ++)   {    ftempabs = fabs(*input++);     level = (ftempabs >= level)? wpt[0] *(level − ftempabs) +     ftempabs : wpt[1] * (level − ftempabs) +ftempabs;     GR = 1.0;     if (level * invT > 1.0)     {      excessGain = level *invT;       interp = excessGain −trunc(excessGain);       j = (int) trunc(excessGain) − 1;       if (j <99)       {         GR = table[index][j] + interp * (table[index][j+1] −        table[index][j]);         // table[ ][ ] is the exponentiationtable       }       else       {         GR = table[index][99];       }    }     *output++ = *input++ * GR;   } }

The compressor function takes as input arguments pointers to input,output, and wpt arrays and an integer, index. The input and outputarrays are used for the blocks of input and output data, respectively.The first line of code,

static float level;

allocates static storage for a value called “level” which maintains thecomputed signal level between calls to the function. This is because thelevel is something that needs to be tracked continuously, for the entireduration of the program, not just during execution of a single block ofdata.

The next line of code,

float interp, GR, excessGain, L, invT, ftempabs;

allocates temporary storage for a few quantities that are used duringthe computation of the compressor algorithm; these quantities are onlyneeded on a per-block basis and can be discarded after each pass throughthe function.

The next line of code,

invT=wpt[2];

extracts the inverse of the compressor threshold, which is stored inwpt[2], which is the third element of the wpt array. The other elementsof the wpt array include the attack time, the release time, and thecompressor ratio.

The next line of code indicates that the compressor loop is repeatedNSAMPLES times. The next two lines of code implement the levelcomputation as per the equations above. To see this, notice that theline

level=(ftempabs>=level)?wpt[0]*(level˜ftempabs)+ftempbas:wpt[1]*(level−ftempabs)+ftempabs;

is equivalent to the expanded statement

if (ftempabs >= level) {   level = wpt[0] * (level − ftempabs) +ftempabs; } else {   level = wpt[1] * (level − ftempabs) + ftempabs;which is what is needed to carry out the above necessary equation, withwpt[0] storing the attack constant aatt and wpt[1] storing the releaseconstant αrel.

Next, it can be assumed that the gain reduction, GR, is equal to unity.Then the comparison

if(level*invT>1.0)

is performed, which is the same thing as asking if level >T, i.e., thesignal level is over the threshold. If it is not, nothing is done. If itis, the gain reduction is computed. First, the excess gain is computedas

excessGain=level*invT;

as calculated using the equations above. The next two statements,

interp=excessGain−trunc(excessGain);

j=(int)trunc(excessGain)−1;

compute the value of index into the table of exponentiated values, asper the equations above. The next lines,

if (j < 99) {   GR = table[index][j] + interp * (table[index][j+1] −table [index][j]);   // table [ ] [ ] is the exponentiation table } else{   GR = table [index] [99];implement the interpolation explained above. The two-dimensional array,“table,” is parameterized by two indices: index and j. The value j issimply the nearest integer value of the excess gain. The table hasvalues equal to

${{{table}\lbrack{index}\rbrack}\lbrack j\rbrack} = {(j)\frac{1 - {index}}{index}}$

which can be recognized as the necessary value from the equations above,where the “floor” operation isn't needed because j is an integer value.Finally, the input is scaled by the computed gain reduction, GR, as per

*output++=*input++*GR;

and the value is written to the next position in the output array, andthe process continues with the next value in the input array until allNSAMPLE values in the input block are exhausted.

It should be noted that in practice, each function described above isgoing to be dealing with arrays of input and output data rather than asingle sample at a time. This doesn't really change the program much, ashinted by the fact that the routines above were passed their inputs andoutputs by reference. Assuming that the algorithm is handed a block ofNSAMPLES in length, the only modification needed to incorporate arraysof data into the bell-filter functions is to incorporate looping intothe code as follows:

void bell(float *xv, float *yv, float gain, float *input, float *output){   float ap_output;   int i;   for (i = 0; i < NSAMPLES; i++)   {    ap_output = geq_b0 * (*input − yv[0]) +     geq_b1 * (xv[1] −yv[1]) + xv[0]     xv[0] = xv[1]; \\ update     xv[1] = *input; \\update     yv[0] = yv[1]; \\update     yv[1] = *output; \\update    *output++ = 0.5 * (1.0−gain) * ap_output + 0.5 *     (1.0+gain) *(*input++);   } }

Digital signal processing method 100 as a whole, may be implemented as aprogram that calls each of the above functions, implemented as follows:

// it is assumed that floatBuffer contains a block of // NSAMPLESsamples of floating-point data. // The following code shows theinstructions that // are executed during a single pass scale(inputGain,floatBuffer, floatBuffer); low_shelf(xv1_ap, yv1_ap, &working_table[0],floatBuffer, floatBuffer); high_shelf(xv2_ap, yv2_ap, &working_table[3],floatBuffer, floatBuffer); compressor(floatBuffer, floatBuffer,&working_table[6], ratio1Index); low_shelf(xv3_ap_left, yv3_ap_left,xv3_ap_right, yv3_ap_right, &working_table[11], floatBuffer,floatBuffer); high_shelf(xv4_ap_left, yv4_ap_left, xv4_ap_right,yv4_ap_right, &working_table[14], floatBuffer, floatBuffer);bell(xv1_geq, yv1_geq, &working_table[17], floatBuffer, floatBuffer);bell(xv2_geq, yv2_geq, &working_table[20], floatBuffer, floatBuffer);bell(xv3_geq, yv3_geq, &working_table[23], floatBuffer, floatBuffer);bell(xv4_geq, yv4_geq, &working_table[26], floatBuffer, floatBuffer);bell(xv5_geq, yv5_geq, &working_table[29], floatBuffer, floatBuffer);bell(xv6_geq, yv6_geq, &working_table[32], floatBuffer, floatBuffer);bell(xv7_geq, yv7_geq, &working_table[35], floatBuffer, floatBuffer);bell(xv8_geq, yv8_geq, &working_table[38], floatBuffer, floatBuffer);bell(xv9_geq, yv9_geq, &working_table[41], floatBuffer, floatBuffer);bell(xv10_geq, yv10_geq, &working_table[44], floatBuffer, floatBuffer);bell(xv11_geq, yv11_geq, &working_table[47], floatBuffer, floatBuffer);compressor(floatBuffer, floatBuffer, &working_table[50], ratio1Index);scale(outputGain, floatBuffer, floatBuffer);

As can be seen, there are multiple calls to the scale function, thelow_shelf function, the high_shelf function, the bell function, and thecompressor function. Further, there are references to arrays called xv1,yv1, xv2, yv2, etc. These arrays are state variables that need to bemaintained between calls to the various routines and they store theinternal states of the various filters in the process. There is alsorepeated reference to an array called working_table. This table holdsthe various pre-computed coefficients that are used throughout thealgorithm. Algorithms such as this embodiment of digital signalprocessing method 100 can be subdivided into two parts: the computationof the coefficients that are used in the real-time processing loop andthe real-time processing loop itself. The real-time loop consists ofsimple multiplications and additions, which are simple to perform inreal-time, and the coefficient computation, which requires complicatedtranscendental functions, trigonometric functions, and other operationswhich can not be performed effectively in real-time. Fortunately, thecoefficients are static during run-time and can be pre-computed beforereal-time processing takes place. These coefficients can be specificallycomputed for each audio device in which digital signal processing method100 is to be used. Specifically, when digital signal processing method100 is used in a mobile audio device configured for use in vehicles,these coefficients may be computed separately for each vehicle the audiodevice may be used in to obtain optimum performance and to account forunique acoustic properties in each vehicle such as speaker placement,passenger compartment design, and background noise.

For example, a particular listening environment may produce suchanomalous audio responses such as those from standing waves. Forexample, such standing waves often occur in small listening environmentssuch as an automobile. The length of an automobile, for example, isaround 400 cycles long. In such an environment, some standing waves areset up at this frequency and some below. Standing waves present anamplified signal at their frequency which may present an annoyingacoustic signal. Vehicles of the same size, shape, and of the samecharacteristics, such as cars of the same model, may present the sameanomalies due to their similar size, shape, structural make-up, speakerplacement, speaker quality, and speaker size. The frequency and amountof adjustment performed, in a further embodiment, may be configured inadvance and stored for use in graphic equalizer 107 to reduce anomalousresponses for future presentation in the listening environment.

The “working tables” shown in the previous section all consist ofpre-computed values that are stored in memory and retrieved as needed.This saves a tremendous amount of computation at run-time and allowsdigital signal processing method 100 to run on low-cost digital signalprocessing chips.

It should be noted that the algorithm as detailed in this section iswritten in block form. The program described above is simply a specificsoftware embodiment of digital signal processing method 100, and is notintended to limit the present invention in any way. This softwareembodiment may be programmed upon a computer chip for use in an audiodevice such as, without limitation, a radio, MP3 player, game station,cell phone, television, computer, or public address system. Thissoftware embodiment has the effect of taking an audio signal as input,and outputting that audio signal in a modified form.

While various embodiments of the present invention have been describedabove, it should be understood that they have been presented by way ofexample only, and not of limitation. Likewise, the various diagrams maydepict an example architectural or other configuration for theinvention, which is done to aid in understanding the features andfunctionality that can be included in the invention. The invention isnot restricted to the illustrated example architectures orconfigurations, but the desired features can be implemented using avariety of alternative architectures and configurations. Indeed, it willbe apparent to one of skill in the art how alternative functional,logical or physical partitioning and configurations can be implementedto implement the desired features of the present invention. Also, amultitude of different constituent module names other than thosedepicted herein can be applied to the various partitions. Additionally,with regard to flow diagrams, operational descriptions and methodclaims, the order in which the steps are presented herein shall notmandate that various embodiments be implemented to perform the recitedfunctionality in the same order unless the context dictates otherwise.

Terms and phrases used in this document, and variations thereof, unlessotherwise expressly stated, should be construed as open ended as opposedto limiting. As examples of the foregoing: the term “including” shouldbe read as meaning “including, without limitation” or the like; the term“example” is used to provide exemplary instances of the item indiscussion, not an exhaustive or limiting list thereof; the terms “a” or“an” should be read as meaning “at least one,” “one or more” or thelike; and adjectives such as “conventional,” “traditional,” “normal,”“standard,” “known” and terms of similar meaning should not be construedas limiting the item described to a given time period or to an itemavailable as of a given time, but instead should be read to encompassconventional, traditional, normal, or standard technologies that may beavailable or known now or at any time in the future. Likewise, wherethis document refers to technologies that would be apparent or known toone of ordinary skill in the art, such technologies encompass thoseapparent or known to the skilled artisan now or at any time in thefuture.

A group of items linked with the conjunction “and” should not be read asrequiring that each and every one of those items be present in thegrouping, but rather should be read as “and/or” unless expressly statedotherwise. Similarly, a group of items linked with the conjunction “or”should not be read as requiring mutual exclusivity among that group, butrather should also be read as “and/or” unless expressly statedotherwise. Furthermore, although items, elements or components of theinvention may be described or claimed in the singular, the plural iscontemplated to be within the scope thereof unless limitation to thesingular is explicitly stated.

The presence of broadening words and phrases such as “one or more,” “atleast,” “but not limited to” or other like phrases in some instancesshall not be read to mean that the narrower case is intended or requiredin instances where such broadening phrases may be absent. The use of theterm “module” does not imply that the components or functionalitydescribed or claimed as part of the module are all configured in acommon package. Indeed, any or all of the various components of amodule, whether control logic or other components, can be combined in asingle package or separately maintained and can further be distributedin multiple groupings or packages or across multiple locations.

Additionally, the various embodiments set forth herein are described interms of exemplary block diagrams, flow charts and other illustrations.As will become apparent to one of ordinary skill in the art afterreading this document, the illustrated embodiments and their variousalternatives can be implemented without confinement to the illustratedexamples. For example, block diagrams and their accompanying descriptionshould not be construed as mandating a particular architecture orconfiguration.

1. A method comprising: receiving a profile comprising a plurality offilter equalizing coefficients; configuring a plurality of filters of agraphic equalizer using the plurality of filter equalizing coefficientsfrom the profile; receiving a first signal for processing; adjusting theplurality of filters using a first gain; equalizing the first signalusing the plurality of filters of the graphic equalizer; outputting thefirst signal; receiving a second signal for processing; adjusting theplurality of filters, previously configured using the filtercoefficients from the profile, using a second gain; equalizing thesecond plurality of frequencies of the second signal with the pluralityof filters of the graphic equalizer; and outputting the second signal.2. The method of claim 1, wherein the profile comprising the pluralityof filter equalizing coefficients is received from a communicationnetwork.
 3. The method of claim 1, wherein the profile comprising theplurality of filter equalizing coefficients is received from firmware.4. The method of claim 1, wherein the plurality of filters areconfigured using the plurality of filter equalizing coefficients tomodify the first signal to clarify a sound of a voice during a telephonecommunication.
 5. The method of claim 1, wherein the plurality offilters are configured using the plurality of filter equalizingcoefficients to modify the first signal to clarify a sound of a voice ina high noise environment.
 6. The method of claim 1, wherein theplurality of filters are configured using the plurality of filterequalizing coefficients to modify the first signal to adjust a soundassociated with a media file for a handheld device.
 7. The method ofclaim 1, further comprising, prior to equalizing the first signal:adjusting a gain of the first signal; filtering the adjusted firstsignal with a low shelf filter; and compressing the filtered firstsignal with a compressor.
 8. The method of claim 1, further comprising,after equalizing the first signal: compressing the equalized firstsignal with a compressor; and adjusting the gain of the compressed firstsignal.
 9. The method of claim 1, further comprising: filtering thefirst signal with a first low filter; filtering the first signalreceived from the first low shelf filter with a first high shelf filterprior to compressing the filtered signal with a compressor; filteringthe first signal with a second low shelf filter prior to equalizing thefirst signal with the graphic equalizer; and filtering the first signalwith a second high shelf filter after the first signal is filtered withthe second low shelf filter.
 10. The method of claim 1, wherein theplurality of filters of the graphic equalizer comprises eleven cascadingsecond order filters.
 11. The method of claim 10, wherein each of thesecond order filters are bell filters.
 12. A system comprising: agraphic equalizer comprising: a filter module comprising a plurality offilters; a profile module configured to receive a profile comprising aplurality of filter equalizing coefficients; and an equalizing moduleconfigured to configure the plurality of filters using the plurality offilter equalizing coefficients from the profile, to receive first andsecond signals, to adjust the plurality of filters using a first gain,to equalize the first plurality using the plurality of filters of thegraphic equalizer, to output the first signal, to adjust the pluralityof filters, previously configured using the filter equalizingcoefficients from the profile, using a second gain, to equalize thesecond signal using the plurality of filters of the graphic equalizer,and to output the second signal.
 13. The system of claim 12, wherein theprofile comprising the plurality of filter equalizing coefficients isreceived from a communication network.
 14. The system of claim 12,wherein the profile comprising the plurality of filter equalizingcoefficients is received from firmware.
 15. The system of claim 12,wherein the profile module configures the plurality of filters using theplurality of filter equalizing coefficients to modify the first signalto clarify a sound of a voice during a telephone communication.
 16. Thesystem of claim 12, wherein the profile module configures the pluralityof filters using the plurality of filter equalizing coefficients tomodify the first signal to clarify a sound of a voice in a high noiseenvironment.
 17. The system of claim 12, wherein the profile moduleconfigures the plurality of filters using the plurality of filterequalizing coefficients to modify the first signal to adjust a soundassociated with a media file for a handheld device.
 18. The system ofclaim 12, further comprising: a gain amplifier configured to amplify thefirst signal and the second signal; a low shelf filter configured tofilter the amplified first signal and the amplified second signal; and acompressor configured to compress the filtered first signal and thefiltered second signal.
 19. The system of claim 12, further comprising:a compressor configured to compress the equalized first signal and theequalized second signal; and a gain amplifier configured to receive thefirst and second signals from the compressor, amplify a gain of thefirst and second signals, and output the first and second signals. 20.The system of claim 12, further comprising: a first high shelf filterconfigured to filter the first and second signals prior to compressingthe first and second signals with a compressor; a low shelf filterconfigured to receive the first and second signals from the first highshelf filter and to filter the first and second signal prior to thegraphic equalizer equalizing the first and second signals; and a secondhigh shelf filter configured to receive the first and second signalsfrom the low shelf filter and to filter the first and second signals.21. The system of claim 12, wherein the plurality of filters of thegraphic equalizer comprises eleven cascading second order filters.
 22. Amethod comprising: configuring a graphic equalizer using a plurality offilter equalizing coefficients; adjusting the graphic equalizer using afirst gain; processing the first signal with the graphic equalizer;outputting the first signal from the graphic equalizer; adjusting thegraphic equalizer using a second gain; processing the second signal withthe graphic equalizer, the graphic equalizer being previously configuredusing the plurality of filter equalizing coefficients; and outputtingthe second signal from the graphic equalizer.
 23. The method of claim22, further comprising receiving the plurality of filter equalizingcoefficients from a communication network.
 24. The method of claim 22,further comprising receiving the plurality of filter equalizingcoefficients from firmware.
 25. The method of claim 22, furthercomprising: adjusting a gain of the first signal; processing the firstsignal with first low shelf filter; and processing the first signal witha compressor.
 26. A computer readable medium comprising executableinstructions, the instructions being executable by a processor forperforming a method, the method comprising: receiving a profilecomprising a plurality of filter equalizing coefficients; configuring aplurality of filters of a graphic equalizer using the plurality offilter equalizing coefficients from the profile; receiving a firstsignal for processing; adjusting the plurality of filters using a firstgain; equalizing the first signal using the plurality of filters of thegraphic equalizer; outputting the first signal; receiving a secondsignal for processing; adjusting the plurality of filters, previouslyconfigured using the filter coefficients from the profile, using asecond gain; equalizing the second plurality of frequencies of thesecond signal with the plurality of filters of the graphic equalizer;and outputting the second signal.